{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import re"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings;\n",
    "warnings.filterwarnings('ignore');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reading train csv file\n",
    "df = pd.read_csv(r'C:\\Participant_Data_WPPH\\Participant_Data_WPPH\\train.csv')\n",
    "\n",
    "# Reading test csv file\n",
    "test_data = pd.read_csv(r'C:\\Participant_Data_WPPH\\Participant_Data_WPPH\\test.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Creating copies of original dataframes\n",
    "df2 = df.copy()\n",
    "\n",
    "test = test_data.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Uniq Id</th>\n",
       "      <th>Package Name</th>\n",
       "      <th>Package Type</th>\n",
       "      <th>Destination</th>\n",
       "      <th>Itinerary</th>\n",
       "      <th>Places Covered</th>\n",
       "      <th>Travel Date</th>\n",
       "      <th>Hotel Details</th>\n",
       "      <th>Start City</th>\n",
       "      <th>Airline</th>\n",
       "      <th>Flight Stops</th>\n",
       "      <th>Meals</th>\n",
       "      <th>Sightseeing Places Covered</th>\n",
       "      <th>Cancellation Rules</th>\n",
       "      <th>Per Person Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>e788ab76d9d8cf1e6ed2f139645ca5d1</td>\n",
       "      <td>Best of Shimla and Manali Holiday from Delhi</td>\n",
       "      <td>Standard</td>\n",
       "      <td>New Delhi|Shimla|Manali|Chandigarh</td>\n",
       "      <td>1N New Delhi . 2N Shimla . 2N Manali . 1N Chan...</td>\n",
       "      <td>New Delhi|Shimla|Manali|Chandigarh</td>\n",
       "      <td>30-07-2021</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>11509.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>178f892630ce3e335a5a41d5d83937fd</td>\n",
       "      <td>Kashmir Valley vacation</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Srinagar|Pahalgam|Srinagar</td>\n",
       "      <td>1N Srinagar . 2N Pahalgam . 1N Srinagar</td>\n",
       "      <td>Srinagar|Pahalgam|Srinagar</td>\n",
       "      <td>08-12-2021</td>\n",
       "      <td>The Orchard Retreat &amp; Spa:4.6|WelcomHotel Pine...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>IndiGo|IndiGo</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>Dal Lake | Avantipura Ruins | Mughal Gardens ...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>22485.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>f060f2954840503cc2fdaf495357b7df</td>\n",
       "      <td>Might of Mewar- Udaipur and Chittorgarh</td>\n",
       "      <td>Luxury</td>\n",
       "      <td>Udaipur|Chittorgarh</td>\n",
       "      <td>2N Udaipur . 1N Chittorgarh</td>\n",
       "      <td>Udaipur|Chittorgarh</td>\n",
       "      <td>26-04-2021</td>\n",
       "      <td>The Ananta:4.4|juSTa Lake Nahargarh Palace:4</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>IndiGo</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>Lake Pichola | Jag Mandir Palace | Saheliyon ...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>12421.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>32a19a6c171e67448f2346da46c619dc</td>\n",
       "      <td>Colorful Kerala ( Romantic Getaway )</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Munnar|Kumarakom|Allepey|Kovalam and Poovar</td>\n",
       "      <td>2N Munnar . 1N Kumarakom . 1N Allepey . 2N Kov...</td>\n",
       "      <td>Munnar|Kumarakom|Allepey|Kovalam and Poovar</td>\n",
       "      <td>27-08-2021</td>\n",
       "      <td>Elixir Hills Suites Resort &amp; Spa-MMT Holidays ...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>IndiGo</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>Mattupetty Dam | Echo Point | Tata Tea Museum...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>35967.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>107b068aa0ca03bc6248966f594d105f</td>\n",
       "      <td>A Week In Bangkok &amp; Pattaya</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Pattaya|Bangkok</td>\n",
       "      <td>4N Pattaya . 3N Bangkok</td>\n",
       "      <td>Pattaya|Bangkok</td>\n",
       "      <td>12-12-2021</td>\n",
       "      <td>Dusit Thani Pattaya - MMT Special:4.5|Amari Wa...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Spicejet|Go Air</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>Coral Island Tour with Indian Lunch, Join Spe...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>25584.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>3bb074528941b3a6823371f77b07fb0f</td>\n",
       "      <td>Cochin Trip with Visit to Guruvayoor Temple</td>\n",
       "      <td>Deluxe</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>2N Cochin</td>\n",
       "      <td>Cochin</td>\n",
       "      <td>30-09-2021</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>IndiGo</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Dutch Palace | Jewish Synagogue | St. Francis...</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>8512.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>644c71b1a9ccfe6eacc6303be12c1352</td>\n",
       "      <td>Jaipur Holiday</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Jaipur</td>\n",
       "      <td>3N Jaipur</td>\n",
       "      <td>Jaipur</td>\n",
       "      <td>24-01-2021</td>\n",
       "      <td>Ratnawali A Vegetarian Heritage Hotel:4.1</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>IndiGo</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Hawa Mahal | City Palace | Jantar Mantar | Am...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>6848.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>07943295cfdce5cb20861e8369948b1d</td>\n",
       "      <td>Kasol &amp; Manali holiday from Delhi</td>\n",
       "      <td>Deluxe</td>\n",
       "      <td>Kasol|Manali</td>\n",
       "      <td>2N Kasol . 3N Manali</td>\n",
       "      <td>Kasol|Manali</td>\n",
       "      <td>10-12-2021</td>\n",
       "      <td>The Himalayan Village:Four|The Holiday Resorts...</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Pandoh Dam | Hadimba Temple | Tibetan Monaste...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>14454.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>126e12c63233bf11ef2e001a062f2a53</td>\n",
       "      <td>Charismatic Kashmir with Gulmarg</td>\n",
       "      <td>Deluxe</td>\n",
       "      <td>Srinagar|Gulmarg|Pahalgam|Srinagar</td>\n",
       "      <td>1N Srinagar . 1N Gulmarg . 2N Pahalgam . 2N Sr...</td>\n",
       "      <td>Srinagar|Gulmarg|Pahalgam|Srinagar</td>\n",
       "      <td>03-10-2021</td>\n",
       "      <td>California Group of Houseboats:3.6|The Rosewoo...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>IndiGo</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Dal Lake | Gondola Point | Avantipura Ruins |...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>21556.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>72aeb7bac6d5600fe443fca06e3db631</td>\n",
       "      <td>Luxury Getaway to Udaipur - Stay at the Chunda...</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Udaipur</td>\n",
       "      <td>2N Udaipur</td>\n",
       "      <td>Udaipur</td>\n",
       "      <td>15-08-2021</td>\n",
       "      <td>Chunda Palace:4.6</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>IndiGo</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>Lake Pichola | Jag Mandir Palace | Sajjangarh...</td>\n",
       "      <td>This cancellation policy is applicable for boo...</td>\n",
       "      <td>13042.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>e44087e386d00c5267679f8fd307b7f3</td>\n",
       "      <td>Essence of Kerala</td>\n",
       "      <td>Budget</td>\n",
       "      <td>Kovalam and Poovar|Kanyakumari</td>\n",
       "      <td>2N Kovalam and Poovar . 1N Kanyakumari</td>\n",
       "      <td>Kovalam and Poovar|Kanyakumari</td>\n",
       "      <td>02-06-2021</td>\n",
       "      <td>UDAY SAMUDRA LEISURE BEACH HOTEL &amp; SPA-MMT Hol...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Spicejet</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Hawa Beach | Light House Beach | Bhagavathy A...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>10648.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0dbe8654ab9d0e6e7521307cf4e87df5</td>\n",
       "      <td>A Blissful holiday in Kerala</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Cochin|Munnar|Allepey|Kovalam and Poovar</td>\n",
       "      <td>1N Cochin . 2N Munnar . 1N Allepey . 2N Kovala...</td>\n",
       "      <td>Cochin|Munnar|Allepey|Kovalam and Poovar</td>\n",
       "      <td>14-10-2021</td>\n",
       "      <td>Casino Hotel - Cgh Earth-MMT Holidays Special:...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>IndiGo|Spicejet</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>Fort Cochin | Dutch Palace | Jewish Synagogue...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>25902.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>455c47ceb54f32117184ddac1f1d3381</td>\n",
       "      <td>A day visit to Guwahati</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Guwahati</td>\n",
       "      <td>1N Guwahati</td>\n",
       "      <td>Guwahati</td>\n",
       "      <td>15-09-2021</td>\n",
       "      <td>Kiranshree Grand:4.5</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Spicejet</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>Kamakhya Temple</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>12009.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>3429b7d0a59153d4208e1da2c6375fd6</td>\n",
       "      <td>Holiday in Udaipur &amp; Mount Abu by Volvo from A...</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Udaipur|Mount Abu</td>\n",
       "      <td>2N Udaipur . 1N Mount Abu</td>\n",
       "      <td>Udaipur|Mount Abu</td>\n",
       "      <td>21-05-2021</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Lake Pichola | Jag Mandir Palace | Return Vol...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>6911.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>6cd8532dfd379fa163d78c2d6e2fb4b2</td>\n",
       "      <td>Himachal Marvels from Delhi(with Flights)</td>\n",
       "      <td>Deluxe</td>\n",
       "      <td>Chandigarh|Shimla|Manali|Chandigarh</td>\n",
       "      <td>1N Chandigarh . 2N Shimla . 3N Manali . 1N Cha...</td>\n",
       "      <td>Chandigarh|Shimla|Manali|Chandigarh</td>\n",
       "      <td>19-02-2021</td>\n",
       "      <td>Hotel 6 Chandigarh Zirakpur(Medallion):4|Summi...</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Go Air|IndiGo</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Pinjore Gardens | Shimla Church | Scandal poi...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>17323.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>fac47ae77eab1c689848f4b25d45cef8</td>\n",
       "      <td>Drive to Nainital, Kausani and Corbett</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Nainital|Kausani|Corbett</td>\n",
       "      <td>2N Nainital . 1N Kausani . 2N Corbett</td>\n",
       "      <td>Nainital|Kausani|Corbett</td>\n",
       "      <td>29-06-2021</td>\n",
       "      <td>Hotel Maya Regency Bhimtal:3.8|Heritage Resort...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>IndiGo</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Nainital Zoo | Naina devi Temple | Lands End ...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>13890.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>59bb52b95f9f1cbcb5350b50c0c8f9b2</td>\n",
       "      <td>Romantic Getaway - Spectacular Landscapes of K...</td>\n",
       "      <td>Deluxe</td>\n",
       "      <td>Kodaikanal</td>\n",
       "      <td>3N Kodaikanal</td>\n",
       "      <td>Kodaikanal</td>\n",
       "      <td>18-12-2021</td>\n",
       "      <td>Kodai Resort Hotel:4.1</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Air India</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>South India - Convenience Value pack - Sedan ...</td>\n",
       "      <td>This cancellation policy is applicable for boo...</td>\n",
       "      <td>14558.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>7c21b76443e81009f0851635819465f5</td>\n",
       "      <td>Beautiful Kashmir Holiday</td>\n",
       "      <td>Deluxe</td>\n",
       "      <td>Srinagar|Gulmarg|Srinagar</td>\n",
       "      <td>1N Srinagar . 1N Gulmarg . 2N Srinagar</td>\n",
       "      <td>Srinagar|Gulmarg|Srinagar</td>\n",
       "      <td>09-04-2021</td>\n",
       "      <td>California Group of Houseboats:3.6|The Rosewoo...</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Spicejet|Spicejet</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Dal Lake | Gondola Point | Mughal Gardens | C...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>12591.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>d26163e7ff27bf1e8637728c785df0db</td>\n",
       "      <td>A Relaxing Rendezvous in Himachal from Delhi</td>\n",
       "      <td>Luxury</td>\n",
       "      <td>Shimla|Manali|Dharamshala</td>\n",
       "      <td>2N Shimla . 3N Manali . 2N Dharamshala</td>\n",
       "      <td>Shimla|Manali|Dharamshala</td>\n",
       "      <td>27-11-2021</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>Kufri | Mall road | Viceregal Lodge | Pandoh ...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>20739.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>d6d306cb2a359396aefb53ec5fbff2d7</td>\n",
       "      <td>Queen of Hill Stations</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Ooty|Kodaikanal</td>\n",
       "      <td>3N Ooty . 3N Kodaikanal</td>\n",
       "      <td>Ooty|Kodaikanal</td>\n",
       "      <td>22-11-2021</td>\n",
       "      <td>Hotel Meadows Residency:4.4|Hotel Jem Valley:3.8</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Spicejet</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Ooty Lake | Doddabetta Peak | Ooty Botanical ...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>14445.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>1f7667c0aade3e58faca5e41e3d9ec67</td>\n",
       "      <td>Holiday to Kodaikanal, Ooty and Mysore</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Kodaikanal|Ooty|Mysore</td>\n",
       "      <td>2N Kodaikanal . 2N Ooty . 1N Mysore</td>\n",
       "      <td>Kodaikanal|Ooty|Mysore</td>\n",
       "      <td>18-06-2021</td>\n",
       "      <td>The Tamara Kodai:Five|Deccan Park:Three|Countr...</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Go Air</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>Silver Cascade Falls | Kodaikanal Lake | Coak...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>18956.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>b946deebdcada46b09a3c0e6e73585bb</td>\n",
       "      <td>Family Trip to Jaipur with Visit to Salasar Ba...</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Jaipur</td>\n",
       "      <td>2N Jaipur</td>\n",
       "      <td>Jaipur</td>\n",
       "      <td>03-12-2021</td>\n",
       "      <td>RAMADA JAIPUR:4.1</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Spicejet</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>Amer Fort | Jal Mahal | Balaji Temple</td>\n",
       "      <td>This cancellation policy is applicable for boo...</td>\n",
       "      <td>9441.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>478bcd9fea82a32feaf5e8ee747084e1</td>\n",
       "      <td>Three Nights in Golden Triangle (Online Only)</td>\n",
       "      <td>Deluxe</td>\n",
       "      <td>New Delhi|Agra|Jaipur</td>\n",
       "      <td>1N New Delhi . 1N Agra . 1N Jaipur</td>\n",
       "      <td>New Delhi|Agra|Jaipur</td>\n",
       "      <td>10-08-2021</td>\n",
       "      <td>Hotel The Royal Plaza:3.5|The Taj Vilas:4.1|Ni...</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>IndiGo</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Qutab Minar | Rashtrapati Bhawan | Red fort |...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>12733.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>d4396f83afde2cb6d6060e71af32d68a</td>\n",
       "      <td>Best of Dubai - 7 Nights</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Dubai</td>\n",
       "      <td>7N Dubai</td>\n",
       "      <td>Dubai</td>\n",
       "      <td>12-10-2021</td>\n",
       "      <td>Movenpick Hotel Apartments Al Mamzar Dubai - M...</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Emirates|Emirates</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>Entry ticket to Burj Khalifa at the Top - 124...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>43598.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>4a921ab444ed8941ac47ae2023f1f932</td>\n",
       "      <td>Goa 3 Nights - Pure Veg Special</td>\n",
       "      <td>Deluxe</td>\n",
       "      <td>Goa</td>\n",
       "      <td>3N Goa</td>\n",
       "      <td>Goa</td>\n",
       "      <td>09-05-2021</td>\n",
       "      <td>Sharanam Greens Resort:3</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>2580.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>7c1ed47927b846f2484fd03f27895274</td>\n",
       "      <td>A Relaxing Week in North East</td>\n",
       "      <td>Luxury</td>\n",
       "      <td>Gangtok|Pelling|Darjeeling</td>\n",
       "      <td>3N Gangtok . 1N Pelling . 4N Darjeeling</td>\n",
       "      <td>Gangtok|Pelling|Darjeeling</td>\n",
       "      <td>15-07-2021</td>\n",
       "      <td>Lemon Tree Hotel  Gangtok:4.2|The Chumbi Mount...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Spicejet</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>Changu Lake - Excursion | Baba Mandir | Rumte...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>30859.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>657b9aed5b3243275677254e92d85544</td>\n",
       "      <td>Himachal with Amritsar Holiday(with Flights)</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Shimla|Manali|Dharamshala|Dalhousie|Amritsar</td>\n",
       "      <td>2N Shimla . 3N Manali . 2N Dharamshala . 2N Da...</td>\n",
       "      <td>Shimla|Manali|Dharamshala|Dalhousie|Amritsar</td>\n",
       "      <td>24-12-2021</td>\n",
       "      <td>The Oberoi Cecil:4.8|Solang Valley Resort:3.8|...</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Spicejet|Air India|Air India</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>Himalayan Zoo | Mall road | Shimla Church | S...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>41496.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>d8c2cf32f9feb23785e619306e565159</td>\n",
       "      <td>Gangtok Pelling &amp; Darjeeling Holidays with Sha...</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Gangtok|Pelling|Darjeeling</td>\n",
       "      <td>3N Gangtok . 1N Pelling . 2N Darjeeling</td>\n",
       "      <td>Gangtok|Pelling|Darjeeling</td>\n",
       "      <td>13-04-2021</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>Baba Mandir | Changu Lake | Rumtek Monastery ...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>13465.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>09a9a35c4634a24b1637c1ae5c86b52a</td>\n",
       "      <td>A tour to Coorg, Ooty and Bandipur</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Coorg|Ooty|Bandipur</td>\n",
       "      <td>3N Coorg . 2N Ooty . 1N Bandipur</td>\n",
       "      <td>Coorg|Ooty|Bandipur</td>\n",
       "      <td>18-02-2021</td>\n",
       "      <td>Veerabhoomi Resorts:3.5|Western Valley Resorts...</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Vistara</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Bylakuppe | Tibetan Temple | Dubare Elephant ...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>18719.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>463ba82e2d54a7709bdc2489f0d14532</td>\n",
       "      <td>South India Special (Coorg)</td>\n",
       "      <td>Luxury</td>\n",
       "      <td>Coorg</td>\n",
       "      <td>2N Coorg</td>\n",
       "      <td>Coorg</td>\n",
       "      <td>02-06-2021</td>\n",
       "      <td>The Windflower Resorts &amp; Spa:4</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>IndiGo</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>Tibetan Temple | Abbey falls | Rajaâ€™s Seat ...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>13014.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>a1912824279c2bbbfa3481c584ddb7c4</td>\n",
       "      <td>Golden Triangle with Radisson</td>\n",
       "      <td>Luxury</td>\n",
       "      <td>New Delhi|Agra|Jaipur</td>\n",
       "      <td>2N New Delhi . 1N Agra . 2N Jaipur</td>\n",
       "      <td>New Delhi|Agra|Jaipur</td>\n",
       "      <td>15-04-2021</td>\n",
       "      <td>Radisson Blu Plaza Delhi Airport:4.2|Taj Hotel...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Spicejet</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>Rajghat | Jama Masjid | Red fort | Qutab Mina...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>21751.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>6cbf08446d8919057e7d80fb1e06e723</td>\n",
       "      <td>Mini Kerala - Speed Boat Ride</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Munnar|Thekkady|Allepey</td>\n",
       "      <td>2N Munnar . 1N Thekkady . 1N Allepey</td>\n",
       "      <td>Munnar|Thekkady|Allepey</td>\n",
       "      <td>24-09-2021</td>\n",
       "      <td>Iceberg Hill Hotel-MMT Holidays Special:4|Elep...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>IndiGo</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Valara Waterfalls | Tea Plantation at Devikul...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>12527.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>667806187e7ce471bbbde18af6998064</td>\n",
       "      <td>Take a Break in Shimla - Personal Photoshoot i...</td>\n",
       "      <td>Luxury</td>\n",
       "      <td>Shimla</td>\n",
       "      <td>3N Shimla</td>\n",
       "      <td>Shimla</td>\n",
       "      <td>26-03-2021</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>Shimla Church | Scandal point | Gaeity Theatr...</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>22910.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>85d9d9e6f6b2c60c66a6379d8f25323c</td>\n",
       "      <td>Darjeeling Family Holiday - Exploring Monaster...</td>\n",
       "      <td>Budget</td>\n",
       "      <td>Darjeeling</td>\n",
       "      <td>3N Darjeeling</td>\n",
       "      <td>Darjeeling</td>\n",
       "      <td>18-01-2022</td>\n",
       "      <td>Hotel Shanti Palace:2.4</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>IndiGo|IndiGo</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>Tiger Hill | Himalayan Mountaineering Institu...</td>\n",
       "      <td>This cancellation policy is applicable for boo...</td>\n",
       "      <td>15827.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>4016e8cd09f34aca49d22e2877918c6e</td>\n",
       "      <td>A Relaxing holiday to Kerala - Free Speed Boat...</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Cochin|Munnar|Thekkady|Allepey|Kovalam and Poovar</td>\n",
       "      <td>1N Cochin . 2N Munnar . 1N Thekkady . 1N Allep...</td>\n",
       "      <td>Cochin|Munnar|Thekkady|Allepey|Kovalam and Poovar</td>\n",
       "      <td>27-02-2021</td>\n",
       "      <td>Quality Airport Hotel:4.1|Iceberg Hill Hotel-M...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Spicejet|IndiGo|IndiGo</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Dutch Palace | Jewish Synagogue | St. Francis...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>15795.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>097ecbfe889be8266ac81a8aad061ac3</td>\n",
       "      <td>Holiday in Lovely Himachal from Delhi</td>\n",
       "      <td>Luxury</td>\n",
       "      <td>New Delhi|Shimla|Manali|Chandigarh</td>\n",
       "      <td>2N New Delhi . 2N Shimla . 3N Manali . 1N Chan...</td>\n",
       "      <td>New Delhi|Shimla|Manali|Chandigarh</td>\n",
       "      <td>12-07-2021</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Not Available</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>Rajghat | Jama Masjid | Red fort | Chandni Ch...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>24753.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>d0ccc7cea936010d293601420672dde7</td>\n",
       "      <td>Vibrant North East with Lachung</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Gangtok|Lachung|Gangtok</td>\n",
       "      <td>4N Gangtok . 2N Lachung . 2N Gangtok</td>\n",
       "      <td>Gangtok|Lachung|Gangtok</td>\n",
       "      <td>22-05-2021</td>\n",
       "      <td>Summit Namnang Courtyard &amp; Spa, Gangtok-MMT Ho...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>IndiGo</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Changu Lake | Baba Mandir | Do Drul Chorten S...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>28394.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>a18b935c91bb1c6b9881549dca4c8d8e</td>\n",
       "      <td>Lovely Srinagar with Gulmarg</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Srinagar|Gulmarg</td>\n",
       "      <td>3N Srinagar . 2N Gulmarg</td>\n",
       "      <td>Srinagar|Gulmarg</td>\n",
       "      <td>08-05-2021</td>\n",
       "      <td>The Pride Inn:4.0|Alpine Ridge:3.5</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>IndiGo</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Dal Lake | Mughal Gardens | Cheshma Shahi | N...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>12802.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>59fdbc41932427dff3790a133ee17be7</td>\n",
       "      <td>A Beautiful Journey to South</td>\n",
       "      <td>Deluxe</td>\n",
       "      <td>Mysore|Ooty|Bangalore</td>\n",
       "      <td>1N Mysore . 2N Ooty . 1N Bangalore</td>\n",
       "      <td>Mysore|Ooty|Bangalore</td>\n",
       "      <td>30-03-2021</td>\n",
       "      <td>The Quorum:3.5|Western Valley Resorts:4.1|Rama...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Spicejet</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Mysore Palace | Chamundi Hills | Doddabetta P...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>13521.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>4060de6b8cd3c75689fdf913222ac7e1</td>\n",
       "      <td>Stunning Sri Lanka - with flights</td>\n",
       "      <td>Luxury</td>\n",
       "      <td>Kandy|Bentota|Colombo</td>\n",
       "      <td>2N Kandy . 2N Bentota . 1N Colombo</td>\n",
       "      <td>Kandy|Bentota|Colombo</td>\n",
       "      <td>07-11-2021</td>\n",
       "      <td>Mahaweli Reach-MMT HOLIDAYS SPECIAL:4.0|Citrus...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Spicejet|Spicejet|Spicejet|Spicejet</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>Pinnawala Elephant Orphanage | Peradeniya Bot...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>24580.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>1acaaa9ec53098533f5999e2ff4de155</td>\n",
       "      <td>Kerala for Wildlife Lovers - Exploring Periyar...</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Thekkady|Cochin</td>\n",
       "      <td>2N Thekkady . 1N Cochin</td>\n",
       "      <td>Thekkady|Cochin</td>\n",
       "      <td>08-10-2021</td>\n",
       "      <td>Hotel Sandra Palace-MMT Holidays Special:4.1|Q...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Air India</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Periyar wildlife Sanctuary | Fort Cochin | Du...</td>\n",
       "      <td>This cancellation policy is applicable for boo...</td>\n",
       "      <td>10039.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>b50776516822839edd4d9b6db0158c35</td>\n",
       "      <td>North East Wonders - Darjeeling and Gangtok Sp...</td>\n",
       "      <td>Luxury</td>\n",
       "      <td>Darjeeling|Gangtok</td>\n",
       "      <td>4N Darjeeling . 2N Gangtok</td>\n",
       "      <td>Darjeeling|Gangtok</td>\n",
       "      <td>22-11-2021</td>\n",
       "      <td>Summit Hermon Hotel and Spa-MMT HOLIDAY SPECIA...</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>IndiGo</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>Tiger Hill | Himalayan Mountaineering Institu...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>27722.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>427c986012347caf1f5b44229a918104</td>\n",
       "      <td>Refreshing Parwanoo with Shimla from Delhi(wit...</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Parwanoo|Shimla</td>\n",
       "      <td>1N Parwanoo . 2N Shimla</td>\n",
       "      <td>Parwanoo|Shimla</td>\n",
       "      <td>30-03-2021</td>\n",
       "      <td>The Terrace:Four|Clarkes Hotel, A grand herita...</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Go Air</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>Kufri | Viceregal Lodge | Mall road</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>16653.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>b384fde134a44fc3f0b7bb98d361c7c7</td>\n",
       "      <td>A short trip to Nameri and Guwahati</td>\n",
       "      <td>Deluxe</td>\n",
       "      <td>Nameri|Guwahati</td>\n",
       "      <td>2N Nameri . 1N Guwahati</td>\n",
       "      <td>Nameri|Guwahati</td>\n",
       "      <td>01-05-2021</td>\n",
       "      <td>Hotel KRC Palace:4.3|Hotel Dynasty:3.7</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Spicejet</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Nameri National Park | Kamakhya Temple | Assa...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>14085.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>9a4cfd3a08b761944c292fa80a8fcdab</td>\n",
       "      <td>Awesome Mysore Wayanad Adventure - Trek to Che...</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Mysore|Wayanad</td>\n",
       "      <td>1N Mysore . 2N Wayanad</td>\n",
       "      <td>Mysore|Wayanad</td>\n",
       "      <td>08-05-2021</td>\n",
       "      <td>Hotel Roopa:3.5|Planet Green Plantation Resort...</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Vistara</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Tipu Sultan's Summer Palace | Brindavan Garde...</td>\n",
       "      <td>This cancellation policy is applicable for boo...</td>\n",
       "      <td>10929.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>8bcfddd5a1eb3354f7dc1038840bf0d5</td>\n",
       "      <td>Lovely Himachal from Delhi(with Flights)</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Chandigarh|Shimla|Manali|Parwanoo</td>\n",
       "      <td>1N Chandigarh . 2N Shimla . 3N Manali . 1N Par...</td>\n",
       "      <td>Chandigarh|Shimla|Manali|Parwanoo</td>\n",
       "      <td>02-09-2021</td>\n",
       "      <td>Red Fox Hotel Chandigarh:Three|Hotel Baljees R...</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>Vistara</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Rock Garden | Rose Garden | Kufri | Viceregal...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>16384.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>641b37bb7a32f7500caa86eabad536ec</td>\n",
       "      <td>Majestic Darjeeling, Gangtok &amp; Kalimpong Holidays</td>\n",
       "      <td>Deluxe</td>\n",
       "      <td>Darjeeling|Gangtok|Kalimpong</td>\n",
       "      <td>2N Darjeeling . 2N Gangtok . 1N Kalimpong</td>\n",
       "      <td>Darjeeling|Gangtok|Kalimpong</td>\n",
       "      <td>03-08-2021</td>\n",
       "      <td>Ramada by Wyndham Darjeeling Gandhi Road:Four|...</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>IndiGo</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>Tiger Hill | Himalayan Mountaineering Institu...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>24800.5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>496a618b5b39fc4da4020173fdef2920</td>\n",
       "      <td>A short weekend in North East - Darjeeling to ...</td>\n",
       "      <td>Luxury</td>\n",
       "      <td>Darjeeling|Gangtok</td>\n",
       "      <td>1N Darjeeling . 2N Gangtok</td>\n",
       "      <td>Darjeeling|Gangtok</td>\n",
       "      <td>17-09-2021</td>\n",
       "      <td>Ramada by Wyndham Darjeeling Gandhi Road:4.4|M...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>IndiGo</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>Tiger Hill | Himalayan Mountaineering Institu...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>22166.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>5f2c43b92b1368cb55a7d26c20e66fac</td>\n",
       "      <td>Family Holiday in Bali and Singapore - 6 Nights</td>\n",
       "      <td>Standard</td>\n",
       "      <td>Bali|Singapore</td>\n",
       "      <td>3N Bali . 3N Singapore</td>\n",
       "      <td>Bali|Singapore</td>\n",
       "      <td>05-01-2022</td>\n",
       "      <td>Best Western Kuta Beach-MMT Special:3.0|Qualit...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>Thai Airways|Thai Airways|AirAsia Indonesia|Sr...</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>Guided Kintamani Tour with Indian Lunch and P...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>49045.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>b6c222c684f16a72ad32aff99e1373a1</td>\n",
       "      <td>Himalayan Glitter - Lunch at Darjeeling Tea Es...</td>\n",
       "      <td>Premium</td>\n",
       "      <td>Gangtok|Pelling|Darjeeling</td>\n",
       "      <td>3N Gangtok . 1N Pelling . 2N Darjeeling</td>\n",
       "      <td>Gangtok|Pelling|Darjeeling</td>\n",
       "      <td>08-12-2021</td>\n",
       "      <td>Mayfair Spa Resort &amp; Casino:4.5|The Chumbi Mou...</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>IndiGo|IndiGo</td>\n",
       "      <td>0</td>\n",
       "      <td>5</td>\n",
       "      <td>Baba Mandir | Changu Lake - Excursion | Rumte...</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>39963.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Uniq Id  \\\n",
       "0   e788ab76d9d8cf1e6ed2f139645ca5d1   \n",
       "1   178f892630ce3e335a5a41d5d83937fd   \n",
       "2   f060f2954840503cc2fdaf495357b7df   \n",
       "3   32a19a6c171e67448f2346da46c619dc   \n",
       "4   107b068aa0ca03bc6248966f594d105f   \n",
       "5   3bb074528941b3a6823371f77b07fb0f   \n",
       "6   644c71b1a9ccfe6eacc6303be12c1352   \n",
       "7   07943295cfdce5cb20861e8369948b1d   \n",
       "8   126e12c63233bf11ef2e001a062f2a53   \n",
       "9   72aeb7bac6d5600fe443fca06e3db631   \n",
       "10  e44087e386d00c5267679f8fd307b7f3   \n",
       "11  0dbe8654ab9d0e6e7521307cf4e87df5   \n",
       "12  455c47ceb54f32117184ddac1f1d3381   \n",
       "13  3429b7d0a59153d4208e1da2c6375fd6   \n",
       "14  6cd8532dfd379fa163d78c2d6e2fb4b2   \n",
       "15  fac47ae77eab1c689848f4b25d45cef8   \n",
       "16  59bb52b95f9f1cbcb5350b50c0c8f9b2   \n",
       "17  7c21b76443e81009f0851635819465f5   \n",
       "18  d26163e7ff27bf1e8637728c785df0db   \n",
       "19  d6d306cb2a359396aefb53ec5fbff2d7   \n",
       "20  1f7667c0aade3e58faca5e41e3d9ec67   \n",
       "21  b946deebdcada46b09a3c0e6e73585bb   \n",
       "22  478bcd9fea82a32feaf5e8ee747084e1   \n",
       "23  d4396f83afde2cb6d6060e71af32d68a   \n",
       "24  4a921ab444ed8941ac47ae2023f1f932   \n",
       "25  7c1ed47927b846f2484fd03f27895274   \n",
       "26  657b9aed5b3243275677254e92d85544   \n",
       "27  d8c2cf32f9feb23785e619306e565159   \n",
       "28  09a9a35c4634a24b1637c1ae5c86b52a   \n",
       "29  463ba82e2d54a7709bdc2489f0d14532   \n",
       "30  a1912824279c2bbbfa3481c584ddb7c4   \n",
       "31  6cbf08446d8919057e7d80fb1e06e723   \n",
       "32  667806187e7ce471bbbde18af6998064   \n",
       "33  85d9d9e6f6b2c60c66a6379d8f25323c   \n",
       "34  4016e8cd09f34aca49d22e2877918c6e   \n",
       "35  097ecbfe889be8266ac81a8aad061ac3   \n",
       "36  d0ccc7cea936010d293601420672dde7   \n",
       "37  a18b935c91bb1c6b9881549dca4c8d8e   \n",
       "38  59fdbc41932427dff3790a133ee17be7   \n",
       "39  4060de6b8cd3c75689fdf913222ac7e1   \n",
       "40  1acaaa9ec53098533f5999e2ff4de155   \n",
       "41  b50776516822839edd4d9b6db0158c35   \n",
       "42  427c986012347caf1f5b44229a918104   \n",
       "43  b384fde134a44fc3f0b7bb98d361c7c7   \n",
       "44  9a4cfd3a08b761944c292fa80a8fcdab   \n",
       "45  8bcfddd5a1eb3354f7dc1038840bf0d5   \n",
       "46  641b37bb7a32f7500caa86eabad536ec   \n",
       "47  496a618b5b39fc4da4020173fdef2920   \n",
       "48  5f2c43b92b1368cb55a7d26c20e66fac   \n",
       "49  b6c222c684f16a72ad32aff99e1373a1   \n",
       "\n",
       "                                         Package Name Package Type  \\\n",
       "0        Best of Shimla and Manali Holiday from Delhi     Standard   \n",
       "1                             Kashmir Valley vacation      Premium   \n",
       "2             Might of Mewar- Udaipur and Chittorgarh       Luxury   \n",
       "3                Colorful Kerala ( Romantic Getaway )      Premium   \n",
       "4                         A Week In Bangkok & Pattaya      Premium   \n",
       "5         Cochin Trip with Visit to Guruvayoor Temple       Deluxe   \n",
       "6                                      Jaipur Holiday     Standard   \n",
       "7                   Kasol & Manali holiday from Delhi       Deluxe   \n",
       "8                    Charismatic Kashmir with Gulmarg       Deluxe   \n",
       "9   Luxury Getaway to Udaipur - Stay at the Chunda...      Premium   \n",
       "10                                  Essence of Kerala       Budget   \n",
       "11                       A Blissful holiday in Kerala      Premium   \n",
       "12                            A day visit to Guwahati      Premium   \n",
       "13  Holiday in Udaipur & Mount Abu by Volvo from A...     Standard   \n",
       "14          Himachal Marvels from Delhi(with Flights)       Deluxe   \n",
       "15             Drive to Nainital, Kausani and Corbett     Standard   \n",
       "16  Romantic Getaway - Spectacular Landscapes of K...       Deluxe   \n",
       "17                          Beautiful Kashmir Holiday       Deluxe   \n",
       "18       A Relaxing Rendezvous in Himachal from Delhi       Luxury   \n",
       "19                             Queen of Hill Stations     Standard   \n",
       "20             Holiday to Kodaikanal, Ooty and Mysore      Premium   \n",
       "21  Family Trip to Jaipur with Visit to Salasar Ba...      Premium   \n",
       "22      Three Nights in Golden Triangle (Online Only)       Deluxe   \n",
       "23                           Best of Dubai - 7 Nights      Premium   \n",
       "24                    Goa 3 Nights - Pure Veg Special       Deluxe   \n",
       "25                      A Relaxing Week in North East       Luxury   \n",
       "26       Himachal with Amritsar Holiday(with Flights)      Premium   \n",
       "27  Gangtok Pelling & Darjeeling Holidays with Sha...      Premium   \n",
       "28                 A tour to Coorg, Ooty and Bandipur     Standard   \n",
       "29                        South India Special (Coorg)       Luxury   \n",
       "30                      Golden Triangle with Radisson       Luxury   \n",
       "31                      Mini Kerala - Speed Boat Ride     Standard   \n",
       "32  Take a Break in Shimla - Personal Photoshoot i...       Luxury   \n",
       "33  Darjeeling Family Holiday - Exploring Monaster...       Budget   \n",
       "34  A Relaxing holiday to Kerala - Free Speed Boat...     Standard   \n",
       "35              Holiday in Lovely Himachal from Delhi       Luxury   \n",
       "36                    Vibrant North East with Lachung     Standard   \n",
       "37                       Lovely Srinagar with Gulmarg     Standard   \n",
       "38                       A Beautiful Journey to South       Deluxe   \n",
       "39                  Stunning Sri Lanka - with flights       Luxury   \n",
       "40  Kerala for Wildlife Lovers - Exploring Periyar...     Standard   \n",
       "41  North East Wonders - Darjeeling and Gangtok Sp...       Luxury   \n",
       "42  Refreshing Parwanoo with Shimla from Delhi(wit...      Premium   \n",
       "43                A short trip to Nameri and Guwahati       Deluxe   \n",
       "44  Awesome Mysore Wayanad Adventure - Trek to Che...     Standard   \n",
       "45           Lovely Himachal from Delhi(with Flights)     Standard   \n",
       "46  Majestic Darjeeling, Gangtok & Kalimpong Holidays       Deluxe   \n",
       "47  A short weekend in North East - Darjeeling to ...       Luxury   \n",
       "48    Family Holiday in Bali and Singapore - 6 Nights     Standard   \n",
       "49  Himalayan Glitter - Lunch at Darjeeling Tea Es...      Premium   \n",
       "\n",
       "                                          Destination  \\\n",
       "0                  New Delhi|Shimla|Manali|Chandigarh   \n",
       "1                          Srinagar|Pahalgam|Srinagar   \n",
       "2                                 Udaipur|Chittorgarh   \n",
       "3         Munnar|Kumarakom|Allepey|Kovalam and Poovar   \n",
       "4                                     Pattaya|Bangkok   \n",
       "5                                              Cochin   \n",
       "6                                              Jaipur   \n",
       "7                                        Kasol|Manali   \n",
       "8                  Srinagar|Gulmarg|Pahalgam|Srinagar   \n",
       "9                                             Udaipur   \n",
       "10                     Kovalam and Poovar|Kanyakumari   \n",
       "11           Cochin|Munnar|Allepey|Kovalam and Poovar   \n",
       "12                                           Guwahati   \n",
       "13                                  Udaipur|Mount Abu   \n",
       "14                Chandigarh|Shimla|Manali|Chandigarh   \n",
       "15                           Nainital|Kausani|Corbett   \n",
       "16                                         Kodaikanal   \n",
       "17                          Srinagar|Gulmarg|Srinagar   \n",
       "18                          Shimla|Manali|Dharamshala   \n",
       "19                                    Ooty|Kodaikanal   \n",
       "20                             Kodaikanal|Ooty|Mysore   \n",
       "21                                             Jaipur   \n",
       "22                              New Delhi|Agra|Jaipur   \n",
       "23                                              Dubai   \n",
       "24                                                Goa   \n",
       "25                         Gangtok|Pelling|Darjeeling   \n",
       "26       Shimla|Manali|Dharamshala|Dalhousie|Amritsar   \n",
       "27                         Gangtok|Pelling|Darjeeling   \n",
       "28                                Coorg|Ooty|Bandipur   \n",
       "29                                              Coorg   \n",
       "30                              New Delhi|Agra|Jaipur   \n",
       "31                            Munnar|Thekkady|Allepey   \n",
       "32                                             Shimla   \n",
       "33                                         Darjeeling   \n",
       "34  Cochin|Munnar|Thekkady|Allepey|Kovalam and Poovar   \n",
       "35                 New Delhi|Shimla|Manali|Chandigarh   \n",
       "36                            Gangtok|Lachung|Gangtok   \n",
       "37                                   Srinagar|Gulmarg   \n",
       "38                              Mysore|Ooty|Bangalore   \n",
       "39                              Kandy|Bentota|Colombo   \n",
       "40                                    Thekkady|Cochin   \n",
       "41                                 Darjeeling|Gangtok   \n",
       "42                                    Parwanoo|Shimla   \n",
       "43                                    Nameri|Guwahati   \n",
       "44                                     Mysore|Wayanad   \n",
       "45                  Chandigarh|Shimla|Manali|Parwanoo   \n",
       "46                       Darjeeling|Gangtok|Kalimpong   \n",
       "47                                 Darjeeling|Gangtok   \n",
       "48                                     Bali|Singapore   \n",
       "49                         Gangtok|Pelling|Darjeeling   \n",
       "\n",
       "                                            Itinerary  \\\n",
       "0   1N New Delhi . 2N Shimla . 2N Manali . 1N Chan...   \n",
       "1             1N Srinagar . 2N Pahalgam . 1N Srinagar   \n",
       "2                         2N Udaipur . 1N Chittorgarh   \n",
       "3   2N Munnar . 1N Kumarakom . 1N Allepey . 2N Kov...   \n",
       "4                             4N Pattaya . 3N Bangkok   \n",
       "5                                           2N Cochin   \n",
       "6                                           3N Jaipur   \n",
       "7                                2N Kasol . 3N Manali   \n",
       "8   1N Srinagar . 1N Gulmarg . 2N Pahalgam . 2N Sr...   \n",
       "9                                          2N Udaipur   \n",
       "10             2N Kovalam and Poovar . 1N Kanyakumari   \n",
       "11  1N Cochin . 2N Munnar . 1N Allepey . 2N Kovala...   \n",
       "12                                        1N Guwahati   \n",
       "13                          2N Udaipur . 1N Mount Abu   \n",
       "14  1N Chandigarh . 2N Shimla . 3N Manali . 1N Cha...   \n",
       "15              2N Nainital . 1N Kausani . 2N Corbett   \n",
       "16                                      3N Kodaikanal   \n",
       "17             1N Srinagar . 1N Gulmarg . 2N Srinagar   \n",
       "18             2N Shimla . 3N Manali . 2N Dharamshala   \n",
       "19                            3N Ooty . 3N Kodaikanal   \n",
       "20                2N Kodaikanal . 2N Ooty . 1N Mysore   \n",
       "21                                          2N Jaipur   \n",
       "22                 1N New Delhi . 1N Agra . 1N Jaipur   \n",
       "23                                           7N Dubai   \n",
       "24                                             3N Goa   \n",
       "25            3N Gangtok . 1N Pelling . 4N Darjeeling   \n",
       "26  2N Shimla . 3N Manali . 2N Dharamshala . 2N Da...   \n",
       "27            3N Gangtok . 1N Pelling . 2N Darjeeling   \n",
       "28                   3N Coorg . 2N Ooty . 1N Bandipur   \n",
       "29                                           2N Coorg   \n",
       "30                 2N New Delhi . 1N Agra . 2N Jaipur   \n",
       "31               2N Munnar . 1N Thekkady . 1N Allepey   \n",
       "32                                          3N Shimla   \n",
       "33                                      3N Darjeeling   \n",
       "34  1N Cochin . 2N Munnar . 1N Thekkady . 1N Allep...   \n",
       "35  2N New Delhi . 2N Shimla . 3N Manali . 1N Chan...   \n",
       "36               4N Gangtok . 2N Lachung . 2N Gangtok   \n",
       "37                           3N Srinagar . 2N Gulmarg   \n",
       "38                 1N Mysore . 2N Ooty . 1N Bangalore   \n",
       "39                 2N Kandy . 2N Bentota . 1N Colombo   \n",
       "40                            2N Thekkady . 1N Cochin   \n",
       "41                         4N Darjeeling . 2N Gangtok   \n",
       "42                            1N Parwanoo . 2N Shimla   \n",
       "43                            2N Nameri . 1N Guwahati   \n",
       "44                             1N Mysore . 2N Wayanad   \n",
       "45  1N Chandigarh . 2N Shimla . 3N Manali . 1N Par...   \n",
       "46          2N Darjeeling . 2N Gangtok . 1N Kalimpong   \n",
       "47                         1N Darjeeling . 2N Gangtok   \n",
       "48                             3N Bali . 3N Singapore   \n",
       "49            3N Gangtok . 1N Pelling . 2N Darjeeling   \n",
       "\n",
       "                                       Places Covered Travel Date  \\\n",
       "0                  New Delhi|Shimla|Manali|Chandigarh  30-07-2021   \n",
       "1                          Srinagar|Pahalgam|Srinagar  08-12-2021   \n",
       "2                                 Udaipur|Chittorgarh  26-04-2021   \n",
       "3         Munnar|Kumarakom|Allepey|Kovalam and Poovar  27-08-2021   \n",
       "4                                     Pattaya|Bangkok  12-12-2021   \n",
       "5                                              Cochin  30-09-2021   \n",
       "6                                              Jaipur  24-01-2021   \n",
       "7                                        Kasol|Manali  10-12-2021   \n",
       "8                  Srinagar|Gulmarg|Pahalgam|Srinagar  03-10-2021   \n",
       "9                                             Udaipur  15-08-2021   \n",
       "10                     Kovalam and Poovar|Kanyakumari  02-06-2021   \n",
       "11           Cochin|Munnar|Allepey|Kovalam and Poovar  14-10-2021   \n",
       "12                                           Guwahati  15-09-2021   \n",
       "13                                  Udaipur|Mount Abu  21-05-2021   \n",
       "14                Chandigarh|Shimla|Manali|Chandigarh  19-02-2021   \n",
       "15                           Nainital|Kausani|Corbett  29-06-2021   \n",
       "16                                         Kodaikanal  18-12-2021   \n",
       "17                          Srinagar|Gulmarg|Srinagar  09-04-2021   \n",
       "18                          Shimla|Manali|Dharamshala  27-11-2021   \n",
       "19                                    Ooty|Kodaikanal  22-11-2021   \n",
       "20                             Kodaikanal|Ooty|Mysore  18-06-2021   \n",
       "21                                             Jaipur  03-12-2021   \n",
       "22                              New Delhi|Agra|Jaipur  10-08-2021   \n",
       "23                                              Dubai  12-10-2021   \n",
       "24                                                Goa  09-05-2021   \n",
       "25                         Gangtok|Pelling|Darjeeling  15-07-2021   \n",
       "26       Shimla|Manali|Dharamshala|Dalhousie|Amritsar  24-12-2021   \n",
       "27                         Gangtok|Pelling|Darjeeling  13-04-2021   \n",
       "28                                Coorg|Ooty|Bandipur  18-02-2021   \n",
       "29                                              Coorg  02-06-2021   \n",
       "30                              New Delhi|Agra|Jaipur  15-04-2021   \n",
       "31                            Munnar|Thekkady|Allepey  24-09-2021   \n",
       "32                                             Shimla  26-03-2021   \n",
       "33                                         Darjeeling  18-01-2022   \n",
       "34  Cochin|Munnar|Thekkady|Allepey|Kovalam and Poovar  27-02-2021   \n",
       "35                 New Delhi|Shimla|Manali|Chandigarh  12-07-2021   \n",
       "36                            Gangtok|Lachung|Gangtok  22-05-2021   \n",
       "37                                   Srinagar|Gulmarg  08-05-2021   \n",
       "38                              Mysore|Ooty|Bangalore  30-03-2021   \n",
       "39                              Kandy|Bentota|Colombo  07-11-2021   \n",
       "40                                    Thekkady|Cochin  08-10-2021   \n",
       "41                                 Darjeeling|Gangtok  22-11-2021   \n",
       "42                                    Parwanoo|Shimla  30-03-2021   \n",
       "43                                    Nameri|Guwahati  01-05-2021   \n",
       "44                                     Mysore|Wayanad  08-05-2021   \n",
       "45                  Chandigarh|Shimla|Manali|Parwanoo  02-09-2021   \n",
       "46                       Darjeeling|Gangtok|Kalimpong  03-08-2021   \n",
       "47                                 Darjeeling|Gangtok  17-09-2021   \n",
       "48                                     Bali|Singapore  05-01-2022   \n",
       "49                         Gangtok|Pelling|Darjeeling  08-12-2021   \n",
       "\n",
       "                                        Hotel Details Start City  \\\n",
       "0                                       Not Available     Mumbai   \n",
       "1   The Orchard Retreat & Spa:4.6|WelcomHotel Pine...  New Delhi   \n",
       "2        The Ananta:4.4|juSTa Lake Nahargarh Palace:4  New Delhi   \n",
       "3   Elixir Hills Suites Resort & Spa-MMT Holidays ...  New Delhi   \n",
       "4   Dusit Thani Pattaya - MMT Special:4.5|Amari Wa...  New Delhi   \n",
       "5                                       Not Available     Mumbai   \n",
       "6           Ratnawali A Vegetarian Heritage Hotel:4.1  New Delhi   \n",
       "7   The Himalayan Village:Four|The Holiday Resorts...     Mumbai   \n",
       "8   California Group of Houseboats:3.6|The Rosewoo...  New Delhi   \n",
       "9                                   Chunda Palace:4.6     Mumbai   \n",
       "10  UDAY SAMUDRA LEISURE BEACH HOTEL & SPA-MMT Hol...  New Delhi   \n",
       "11  Casino Hotel - Cgh Earth-MMT Holidays Special:...  New Delhi   \n",
       "12                               Kiranshree Grand:4.5  New Delhi   \n",
       "13                                      Not Available  New Delhi   \n",
       "14  Hotel 6 Chandigarh Zirakpur(Medallion):4|Summi...     Mumbai   \n",
       "15  Hotel Maya Regency Bhimtal:3.8|Heritage Resort...  New Delhi   \n",
       "16                             Kodai Resort Hotel:4.1  New Delhi   \n",
       "17  California Group of Houseboats:3.6|The Rosewoo...     Mumbai   \n",
       "18                                      Not Available     Mumbai   \n",
       "19   Hotel Meadows Residency:4.4|Hotel Jem Valley:3.8     Mumbai   \n",
       "20  The Tamara Kodai:Five|Deccan Park:Three|Countr...     Mumbai   \n",
       "21                                  RAMADA JAIPUR:4.1  New Delhi   \n",
       "22  Hotel The Royal Plaza:3.5|The Taj Vilas:4.1|Ni...     Mumbai   \n",
       "23  Movenpick Hotel Apartments Al Mamzar Dubai - M...     Mumbai   \n",
       "24                           Sharanam Greens Resort:3  New Delhi   \n",
       "25  Lemon Tree Hotel  Gangtok:4.2|The Chumbi Mount...  New Delhi   \n",
       "26  The Oberoi Cecil:4.8|Solang Valley Resort:3.8|...     Mumbai   \n",
       "27                                      Not Available     Mumbai   \n",
       "28  Veerabhoomi Resorts:3.5|Western Valley Resorts...     Mumbai   \n",
       "29                     The Windflower Resorts & Spa:4  New Delhi   \n",
       "30  Radisson Blu Plaza Delhi Airport:4.2|Taj Hotel...  New Delhi   \n",
       "31  Iceberg Hill Hotel-MMT Holidays Special:4|Elep...  New Delhi   \n",
       "32                                      Not Available     Mumbai   \n",
       "33                            Hotel Shanti Palace:2.4  New Delhi   \n",
       "34  Quality Airport Hotel:4.1|Iceberg Hill Hotel-M...  New Delhi   \n",
       "35                                      Not Available  New Delhi   \n",
       "36  Summit Namnang Courtyard & Spa, Gangtok-MMT Ho...  New Delhi   \n",
       "37                 The Pride Inn:4.0|Alpine Ridge:3.5  New Delhi   \n",
       "38  The Quorum:3.5|Western Valley Resorts:4.1|Rama...  New Delhi   \n",
       "39  Mahaweli Reach-MMT HOLIDAYS SPECIAL:4.0|Citrus...  New Delhi   \n",
       "40  Hotel Sandra Palace-MMT Holidays Special:4.1|Q...  New Delhi   \n",
       "41  Summit Hermon Hotel and Spa-MMT HOLIDAY SPECIA...     Mumbai   \n",
       "42  The Terrace:Four|Clarkes Hotel, A grand herita...     Mumbai   \n",
       "43             Hotel KRC Palace:4.3|Hotel Dynasty:3.7  New Delhi   \n",
       "44  Hotel Roopa:3.5|Planet Green Plantation Resort...     Mumbai   \n",
       "45  Red Fox Hotel Chandigarh:Three|Hotel Baljees R...     Mumbai   \n",
       "46  Ramada by Wyndham Darjeeling Gandhi Road:Four|...     Mumbai   \n",
       "47  Ramada by Wyndham Darjeeling Gandhi Road:4.4|M...  New Delhi   \n",
       "48  Best Western Kuta Beach-MMT Special:3.0|Qualit...  New Delhi   \n",
       "49  Mayfair Spa Resort & Casino:4.5|The Chumbi Mou...  New Delhi   \n",
       "\n",
       "                                              Airline  Flight Stops  Meals  \\\n",
       "0                                       Not Available             2      3   \n",
       "1                                       IndiGo|IndiGo             0      5   \n",
       "2                                              IndiGo             0      4   \n",
       "3                                              IndiGo             0      5   \n",
       "4                                     Spicejet|Go Air             0      5   \n",
       "5                                              IndiGo             1      3   \n",
       "6                                              IndiGo             2      3   \n",
       "7                                       Not Available             1      3   \n",
       "8                                              IndiGo             1      3   \n",
       "9                                              IndiGo             0      5   \n",
       "10                                           Spicejet             2      2   \n",
       "11                                    IndiGo|Spicejet             0      5   \n",
       "12                                           Spicejet             0      5   \n",
       "13                                      Not Available             2      3   \n",
       "14                                      Go Air|IndiGo             1      3   \n",
       "15                                             IndiGo             2      3   \n",
       "16                                          Air India             1      3   \n",
       "17                                  Spicejet|Spicejet             1      3   \n",
       "18                                      Not Available             0      4   \n",
       "19                                           Spicejet             2      3   \n",
       "20                                             Go Air             0      5   \n",
       "21                                           Spicejet             0      5   \n",
       "22                                             IndiGo             1      3   \n",
       "23                                  Emirates|Emirates             0      5   \n",
       "24                                      Not Available             1      3   \n",
       "25                                           Spicejet             0      4   \n",
       "26                       Spicejet|Air India|Air India             0      5   \n",
       "27                                      Not Available             0      5   \n",
       "28                                            Vistara             2      3   \n",
       "29                                             IndiGo             0      4   \n",
       "30                                           Spicejet             0      4   \n",
       "31                                             IndiGo             2      3   \n",
       "32                                      Not Available             0      4   \n",
       "33                                      IndiGo|IndiGo             2      2   \n",
       "34                             Spicejet|IndiGo|IndiGo             2      3   \n",
       "35                                      Not Available             0      4   \n",
       "36                                             IndiGo             2      3   \n",
       "37                                             IndiGo             2      3   \n",
       "38                                           Spicejet             1      3   \n",
       "39                Spicejet|Spicejet|Spicejet|Spicejet             0      4   \n",
       "40                                          Air India             2      3   \n",
       "41                                             IndiGo             0      4   \n",
       "42                                             Go Air             0      5   \n",
       "43                                           Spicejet             1      3   \n",
       "44                                            Vistara             2      3   \n",
       "45                                            Vistara             2      3   \n",
       "46                                             IndiGo             1      3   \n",
       "47                                             IndiGo             0      4   \n",
       "48  Thai Airways|Thai Airways|AirAsia Indonesia|Sr...             2      3   \n",
       "49                                      IndiGo|IndiGo             0      5   \n",
       "\n",
       "                           Sightseeing Places Covered  \\\n",
       "0                                       Not Available   \n",
       "1    Dal Lake | Avantipura Ruins | Mughal Gardens ...   \n",
       "2    Lake Pichola | Jag Mandir Palace | Saheliyon ...   \n",
       "3    Mattupetty Dam | Echo Point | Tata Tea Museum...   \n",
       "4    Coral Island Tour with Indian Lunch, Join Spe...   \n",
       "5    Dutch Palace | Jewish Synagogue | St. Francis...   \n",
       "6    Hawa Mahal | City Palace | Jantar Mantar | Am...   \n",
       "7    Pandoh Dam | Hadimba Temple | Tibetan Monaste...   \n",
       "8    Dal Lake | Gondola Point | Avantipura Ruins |...   \n",
       "9    Lake Pichola | Jag Mandir Palace | Sajjangarh...   \n",
       "10   Hawa Beach | Light House Beach | Bhagavathy A...   \n",
       "11   Fort Cochin | Dutch Palace | Jewish Synagogue...   \n",
       "12                                   Kamakhya Temple    \n",
       "13   Lake Pichola | Jag Mandir Palace | Return Vol...   \n",
       "14   Pinjore Gardens | Shimla Church | Scandal poi...   \n",
       "15   Nainital Zoo | Naina devi Temple | Lands End ...   \n",
       "16   South India - Convenience Value pack - Sedan ...   \n",
       "17   Dal Lake | Gondola Point | Mughal Gardens | C...   \n",
       "18   Kufri | Mall road | Viceregal Lodge | Pandoh ...   \n",
       "19   Ooty Lake | Doddabetta Peak | Ooty Botanical ...   \n",
       "20   Silver Cascade Falls | Kodaikanal Lake | Coak...   \n",
       "21             Amer Fort | Jal Mahal | Balaji Temple    \n",
       "22   Qutab Minar | Rashtrapati Bhawan | Red fort |...   \n",
       "23   Entry ticket to Burj Khalifa at the Top - 124...   \n",
       "24                                      Not Available   \n",
       "25   Changu Lake - Excursion | Baba Mandir | Rumte...   \n",
       "26   Himalayan Zoo | Mall road | Shimla Church | S...   \n",
       "27   Baba Mandir | Changu Lake | Rumtek Monastery ...   \n",
       "28   Bylakuppe | Tibetan Temple | Dubare Elephant ...   \n",
       "29   Tibetan Temple | Abbey falls | Rajaâ€™s Seat ...   \n",
       "30   Rajghat | Jama Masjid | Red fort | Qutab Mina...   \n",
       "31   Valara Waterfalls | Tea Plantation at Devikul...   \n",
       "32   Shimla Church | Scandal point | Gaeity Theatr...   \n",
       "33   Tiger Hill | Himalayan Mountaineering Institu...   \n",
       "34   Dutch Palace | Jewish Synagogue | St. Francis...   \n",
       "35   Rajghat | Jama Masjid | Red fort | Chandni Ch...   \n",
       "36   Changu Lake | Baba Mandir | Do Drul Chorten S...   \n",
       "37   Dal Lake | Mughal Gardens | Cheshma Shahi | N...   \n",
       "38   Mysore Palace | Chamundi Hills | Doddabetta P...   \n",
       "39   Pinnawala Elephant Orphanage | Peradeniya Bot...   \n",
       "40   Periyar wildlife Sanctuary | Fort Cochin | Du...   \n",
       "41   Tiger Hill | Himalayan Mountaineering Institu...   \n",
       "42               Kufri | Viceregal Lodge | Mall road    \n",
       "43   Nameri National Park | Kamakhya Temple | Assa...   \n",
       "44   Tipu Sultan's Summer Palace | Brindavan Garde...   \n",
       "45   Rock Garden | Rose Garden | Kufri | Viceregal...   \n",
       "46   Tiger Hill | Himalayan Mountaineering Institu...   \n",
       "47   Tiger Hill | Himalayan Mountaineering Institu...   \n",
       "48   Guided Kintamani Tour with Indian Lunch and P...   \n",
       "49   Baba Mandir | Changu Lake - Excursion | Rumte...   \n",
       "\n",
       "                                   Cancellation Rules  Per Person Price  \n",
       "0                                       Not Available           11509.0  \n",
       "1   Cancellation any time after making the 1st pay...           22485.5  \n",
       "2   Cancellation any time after making the 1st pay...           12421.5  \n",
       "3   Cancellation any time after making the 1st pay...           35967.0  \n",
       "4   Cancellation any time after making the 1st pay...           25584.0  \n",
       "5                                       Not Available            8512.0  \n",
       "6   Cancellation any time after making the 1st pay...            6848.0  \n",
       "7   Cancellation any time after making the 1st pay...           14454.5  \n",
       "8   Cancellation any time after making the 1st pay...           21556.5  \n",
       "9   This cancellation policy is applicable for boo...           13042.0  \n",
       "10  Cancellation any time after making the 1st pay...           10648.5  \n",
       "11  Cancellation any time after making the 1st pay...           25902.0  \n",
       "12  Cancellation any time after making the 1st pay...           12009.5  \n",
       "13  Cancellation any time after making the 1st pay...            6911.0  \n",
       "14  Cancellation any time after making the 1st pay...           17323.0  \n",
       "15  Cancellation any time after making the 1st pay...           13890.0  \n",
       "16  This cancellation policy is applicable for boo...           14558.5  \n",
       "17  Cancellation any time after making the 1st pay...           12591.0  \n",
       "18  Cancellation any time after making the 1st pay...           20739.0  \n",
       "19  Cancellation any time after making the 1st pay...           14445.0  \n",
       "20  Cancellation any time after making the 1st pay...           18956.5  \n",
       "21  This cancellation policy is applicable for boo...            9441.0  \n",
       "22  Cancellation any time after making the 1st pay...           12733.5  \n",
       "23  Cancellation any time after making the 1st pay...           43598.0  \n",
       "24  Cancellation any time after making the 1st pay...            2580.0  \n",
       "25  Cancellation any time after making the 1st pay...           30859.5  \n",
       "26  Cancellation any time after making the 1st pay...           41496.0  \n",
       "27  Cancellation any time after making the 1st pay...           13465.0  \n",
       "28  Cancellation any time after making the 1st pay...           18719.0  \n",
       "29  Cancellation any time after making the 1st pay...           13014.0  \n",
       "30  Cancellation any time after making the 1st pay...           21751.5  \n",
       "31  Cancellation any time after making the 1st pay...           12527.0  \n",
       "32                                      Not Available           22910.0  \n",
       "33  This cancellation policy is applicable for boo...           15827.0  \n",
       "34  Cancellation any time after making the 1st pay...           15795.5  \n",
       "35  Cancellation any time after making the 1st pay...           24753.5  \n",
       "36  Cancellation any time after making the 1st pay...           28394.5  \n",
       "37  Cancellation any time after making the 1st pay...           12802.0  \n",
       "38  Cancellation any time after making the 1st pay...           13521.0  \n",
       "39  Cancellation any time after making the 1st pay...           24580.5  \n",
       "40  This cancellation policy is applicable for boo...           10039.0  \n",
       "41  Cancellation any time after making the 1st pay...           27722.5  \n",
       "42  Cancellation any time after making the 1st pay...           16653.5  \n",
       "43  Cancellation any time after making the 1st pay...           14085.5  \n",
       "44  This cancellation policy is applicable for boo...           10929.5  \n",
       "45  Cancellation any time after making the 1st pay...           16384.0  \n",
       "46  Cancellation any time after making the 1st pay...           24800.5  \n",
       "47  Cancellation any time after making the 1st pay...           22166.0  \n",
       "48  Cancellation any time after making the 1st pay...           49045.0  \n",
       "49  Cancellation any time after making the 1st pay...           39963.0  "
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['Uniq Id', 'Package Name', 'Package Type', 'Destination', 'Itinerary',\n",
       "       'Places Covered', 'Travel Date', 'Hotel Details', 'Start City',\n",
       "       'Airline', 'Flight Stops', 'Meals', 'Sightseeing Places Covered',\n",
       "       'Cancellation Rules', 'Per Person Price'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Per Person Price              0\n",
       "Cancellation Rules            0\n",
       "Sightseeing Places Covered    0\n",
       "Meals                         0\n",
       "Flight Stops                  0\n",
       "Airline                       0\n",
       "Start City                    0\n",
       "Hotel Details                 0\n",
       "Travel Date                   0\n",
       "Places Covered                0\n",
       "Itinerary                     0\n",
       "Destination                   0\n",
       "Package Type                  0\n",
       "Package Name                  0\n",
       "Uniq Id                       0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Checking for null values for all columns\n",
    "df.isnull().sum().sort_values(ascending=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " Total Unique Values are 21000 in Uniq Id\n",
      " Total Unique Values are 2204 in Package Name\n",
      " Total Unique Values are 5 in Package Type\n",
      " Total Unique Values are 565 in Destination\n",
      " Total Unique Values are 966 in Itinerary\n",
      " Total Unique Values are 565 in Places Covered\n",
      " Total Unique Values are 495 in Travel Date\n",
      " Total Unique Values are 6060 in Hotel Details\n",
      " Total Unique Values are 2 in Start City\n",
      " Total Unique Values are 314 in Airline\n",
      " Total Unique Values are 3 in Flight Stops\n",
      " Total Unique Values are 4 in Meals\n",
      " Total Unique Values are 1714 in Sightseeing Places Covered\n",
      " Total Unique Values are 10 in Cancellation Rules\n",
      " Total Unique Values are 17138 in Per Person Price\n"
     ]
    }
   ],
   "source": [
    "for col in df.columns:\n",
    "    print(f' Total Unique Values are {len(df[col].unique())} in {col}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9aeIxU3eJiFRdywX3+EyO/kyq0WWQiMdY25fWyBIRqbqWC+6xmRwDXY1vcUPQXXJobIZCsdToUkSkhbRccI/P5JuixQ1BcOeLriu/i0hVtVxwj83kmqKPG2B9fzAR5+nDupSZiFRPSwV3seSMz+YZaJIW92BXinQyxlMKbhGpopYK7onZPO40TVeJmbG2r1MtbhGpqpYK7vKsycEmOTkJsK6/k93HJsnrBKWIVEmLBXcwS7FZWtwAawc6yRVKvHB8qtGliEiLuGhwm9kGM/umme02s2fM7MP1KGw5xsMWd7P0cQOs69MJShGprkpa3AXg1939GuC1wIfM7OW1LWt5yi3uZhlVAjDYnaK7I6ETlCJSNRcNbnc/6u6Phbcngd3AuloXthzlFnczdZXEzLh2bS9PH1Fwi0h1LKmP28w2ATcC289z321mttPMdo6OjlanuiUam8kRjxm96ea6Itt16/rYfXRCMyhFpCoqDm4z6wb+CfiIu08svN/d73D3re6+dWhoqJo1VmxsJk9/ZxIza8jrX8gr1vUxly+xZ1QnKEXk0lUU3GaWJAjtz7v7vbUtafnGpnP0N1H/dtl16/oAePrwS97vRESWrJJRJQZ8Btjt7n9W+5KWL5ju3jz922WbV3SRScU1skREqqKSFvfrgfcCt5jZrvDr7TWua1nGZ/IMdDVfcMdjwQlKjSwRkWq46Fk8d38IaK5O4wsYm8nxyvV9jS7jvK5b18fdjxykWHLisUgcThFpUi0zc9Ldw6vfNF+LG+C6tX3M5ovs0wlKEblELRPcs/kiuUKpqcZwz/eK8JOAuktE5FK1THA346zJ+a4Y6iadjGlkiYhcstYJ7unmmzU5XzxmvHxNr0aWiMgla5ngHm/yFjcEE3GeOXKaUskbXYqIRFhzzQ2/BKfKKwM24XDAbduHAZjKFpnOFfnkN15gZU+aW2/e2ODKRCSKWiK4t20f5rv7TgLwzWdH2HlgrMEVnd/a/jQAR8bnWNmTbnA1IhJVLdNVMpMrAJBJNe970cqeNImYcWR8ttGliEiEtVBwF+lIxJp6cks8ZqzpS3NYwS0il6Blgns2VySTije6jIta29/JkfFZSq4TlCKyPC0T3DO5QlN3k5St6+8kWyhxKhy+KCKyVC0U3NFpcQPqLhGRZVNw19nK3g7iOkEpIpegZYJ7OhuNrpJELMbqXp2gFJHla4ngLpacbKEUiRY3BP3cR8ZncZ2gFJFlaIngPjuGOxrBvba/k7l8iYOn1OoWkaVrkeAuApDpaP6uEgha3KAlXkVkeVoruCPS4l7V20HcTMEtIsvSEsE9G4Hp7vMl4jFW9XbwzBEFt4gsXUsEd9Ra3BD0cz91+LROUIrIkim4G2TdQCfjM3kOjekEpYgsTYsEd4F4zEjFo/PjrO0LTlDqijgislTRSbpFTGeLdKXimDXvyoALre5Lk4wbTxxScIvI0rREcE9m83Sno3FisiwZj/HytX08NtycF30QkebVEsE9lS3QHZEx3PO9auMATx4aJ18sNboUEYmQ1gjuuQLdHc17keALuenyfubyJXYfnWh0KSISIZEPbndnOluMZIv7po0DADz2orpLRKRykQ/u07N5iu70RKyPG4Kx3Gv60jw6PN7oUkQkQiIf3CemsgCRbHFD0OpWi1tEliLywT0yGQZ3BFvcADddPsDh8VmOT8w1uhQRiYjIB/eJqeDajdFtcfcD6ucWkcpFP7gno91Vcu3aPlKJmMZzi0jFoh/cU1liBp0RWqdkvlQixivX9bFTLW4RqVA0m6nznJjK0t2RIBah6e5l27YPA9CTTvLAcyN8+sF9ZDoS3HrzxgZXJiLN7KItbjO708xGzOzpehS0VCemcpHtJim7Zk0PDjx3fLLRpYhIBFTSVfJZ4G01rmPZRiezkR1RUra2v5PedEIzKEWkIhcNbnd/EDhVh1qWpdxVEmUxM65e3cvzI1MUtG6JiFxE1U5OmtltZrbTzHaOjo5Wa7eLcndOtkBXCQTdJblCiX0nphtdiog0uaoFt7vf4e5b3X3r0NBQtXa7qInZArliie509BaYWmjLUDfJuKm7REQuKtLDAUcjPt19vmQ8xlUre9h9dELXoRSRRUU7uCM++Waha9b0MjFXYNdBLTolIhdWyXDALwDfBV5mZofM7AO1L6syZxaYiviokrJr1/aSisf4h+++2OhSRKSJVTKq5N3uvsbdk+6+3t0/U4/CKhH1lQEXSifj3HT5AF958ggjk1p0SkTOL9JdJSemssRjRiai093P53VbLiNfdD738HCjSxGRJhXt4J7McVlXKpLT3S9kRU8Ht1y9km3bXyRbKDa6HBFpQtEO7qksK7o7Gl1G1b3/9Zs4MZXjvl1HGl2KiDShSAf36FSWFT2tF9xvuHIFV63s5nMP6ySliLxUpIP7xGSWFd2pRpdRdWbGrTdv5IlDp3nmyOlGlyMiTSaywzFKJefEVI6hFuwq2bZ9mGLJScSMP/jK93jnDesAtNyriAARbnGfmMqSK5ZYN9DZ6FJqIpNKcN26PnYdHCdX0MJTInJWZIP70PgsAOtbNLgBXr1pkGyhxFOHNZNSRM6KbnCPlYM70+BKamfTZRmGujvYcUCXNRORsyIc3DMArOtv3Ra3mfHqTQMMn5rh2GnNpBSRQISDe5aBTJKuFpnufiE3bhwgHjN2HGjaa1mISJ1FOrhbuZukrKsjwbVre3n84Bhzec2kFJEIB/fhsZmWPjE536s3DTKXL/EvTx1tdCki0gQiGdzuHra42yO4t6zo4rKuFF94RAtPiUhEg/vEVI5sodQWXSVQPkk5yI4DY+wZmWx0OSLSYJEM7nYYUbLQTZcPkErE+PP/+0KjSxGRBotocIdjuAfbJ7i7OxL8yg9cwVefPMp39p5odDki0kCRDO7D4azJdmpxA/zKm69gw2Anv/PlZ8gXNQ1epF1FMrgPjc3Qn0nSk042upS6Sifj/N5PXMuekSnufGh/o8sRkQaJaHC3z4iS+bZtH+b4RJZrVvdw+9ee5Xe//HSjSxKRBohscLdbN8l879q6gdV9aT6/fZjv7j3Z6HJEpM4iF9zBGO6ZthkKeD7pZJz3v24zg10pfumuHTw+rEWoRNpJ5IL75HSOuXypLbtK5uvqSPCLr9/Mip4OfuHvdrD76ESjSxKROolccB9ug+VcK9XbmeRzH7iZzmSc935mO3tHpxpdkojUQeSC+2AbTr5ZzIbBDJ/7pZtxh5/79HYOnpppdEkiUmORC+7Hh8dJJWJsGepqdClNYdv2YR7Zf4pbb97I2EyOd37q//HX39rb6LJEpIYitZj1tu3D/OtTR1nf38m9jx1udDlNZU1fJ7/wus3c+dB+/vbBfazpS/P2V6whGY/ce7OIXESk/lfP5oocPT3HZrW2z2vjYIb3vW4TZsaH797FG2//Jv/z/ufPrO0iIq0hUi3u/SemcWDLiu5Gl9K0Nq/o4iM/dBUvHJ/kO3tP8smvv8Anv/4CVwx186pNA/z+O64lnYw3ukwRuQQRC+4pEjFjQ5sPBbyYmBkvW93Ly1b3MjaT47EXx3h0eIx7dhzka08f412vWs97Xns5m1fok4tIFEUquPedmGbjZRkS6ret2EAmxVuuWcUPXr2SfaPTHJ+c47PfOcCnH9rPjRv7eeNVQ9y0sZ+ujgQdiRgdiTgdiRgrejrobvHreYpEVWT+Z47P5Dh2eo63XLOy0aVEUsyMK1d2c+XKbl6xro+dB8Z47tgE/+vrL+DnfTy8bHUvN28e5INv2qLhlyJNJDLBvX3/KRzYrP7tS9abTnLL1Su55eqVzOaKHJ+Yo1ByCsUS+fDfk9M5hk/OsO2RYe7eMcyH3nwlH3zTFvWPizSByAT3w/tOkoyrf7vaOlNxNi3S1z02k+NfnjrKn97/PJ96YA+vXN/Pr91yJSt70gxkkvRnUqQS6roSqadIBPe+0Snufewwm1d0qX+7zgYyKd5z8+XsPzHNjgOneHx4jPd+5pFzHpNKxBjMpLjlmpXctHGAa9f2csVQtwJdpEYqCm4zexvwF0Ac+LS7/1FNq5pnfCbHB+7aSTxmvOP6dfV6WVlg84ouNq/oYi6/lkNjs8zkCszkiszkiszmCoxMZvnKriNs2x5ciT74dJRh/WCGDQOdbBjMsH6gk950kkwqTjoZJ5OK05mKk0km6EzFScYNM2vwTyrS/C4a3GYWBz4F/DBwCNhhZve5+/dqWdiJqSxPHhrnrx7Yy+GxWbZ98GaeP65FlBotnYxz5crzn2couTM6meXYxBzHTs9xcjrH3pEpduw/xWy+eNF9x2NGJhmEeWcqTmcyTq5YYi5XZDYffBWKTnc6QW86SW9ngr7OJJlUgmTcSMRiJOJGMhajIxk786bQ1RG+QaTiZFIJ4mZM5wpMZ4OazIKTsYZhBmYWfG/BSV0I/i1/bwSPmf99LAalEhTdKZWcojvF0tmvVCJGVypBpiNOd0eCTCpBInb2Tar8fhXs7dxt85153Lw7beF959nHObuq8HHl1zh320ufe2Z/L91U8T4W/VmXWOf5jlGl3B338PfoTqkU/F0X3fHw9xuz4G81GY8RjxmJWP0bHJW0uF8D7HH3fQBmdjfwTqDqwX3Tx+9naq5AvlTCw6EOybjxJ++6nq2bBhXcTS5mxqreNKt601y//tz75vJFxmfyZAtFcsUS+UIp/NfJFUvnbiuWyBVK5ItOVyrBQGeKZCL4jxIzI1soMpcvMZsrcujULNlC6ZzALJWcfNHJF0sUSucbMyPt6LxvYgss98+lHOArezv49m/esrydLEElwb0OODjv+0PAzQsfZGa3AbeF306Z2XOXXl7gJ/+QFUBULm2uWqsvKnWCaq2FqNTJ87DC/tuya7280gdWEtzne4N6yfuSu98B3FHpCy+Fme1096212He1qdbqi0qdoFprISp1Qv1qreS0/yFgw7zv1wNHalOOiIhcTCXBvQO4ysw2m1kK+FngvtqWJSIiF3LRrhJ3L5jZrwL/RjAc8E53f6bmlZ2rJl0wNaJaqy8qdYJqrYWo1Al1qtXcddZdRCRKNLVNRCRiFNwiIhHT9MFtZm8zs+fMbI+Z/VadXnODmX3TzHab2TNm9uFw+++Z2WEz2xV+vX3ecz4a1vicmb113vZXmdlT4X2ftHCKlZl1mNk94fbtZrbpEuo9EL7GLjPbGW4bNLP7zeyF8N+BRtZqZi+bd9x2mdmEmX2kWY6pmd1pZiNm9vS8bXU5hmb2vvA1XjCz9y2z1k+Y2bNm9qSZfcnM+sPtm8xsdt7x/et61XqBOuvy+67SMb1nXp0HzGxXo4/pGcEUz+b8IjgZuhfYAqSAJ4CX1+F11wA3hbd7gOeBlwO/B/zGeR7/8rC2DmBzWHM8vO8R4PsJxsP/K/Cj4fb/DPx1ePtngXsuod4DwIoF2/4Y+K3w9m8BtzdDrfN+r8cIJhw0xTEF3gTcBDxdz2MIDAL7wn8HwtsDy6j1R4BEePv2ebVumv+4Bfupaa0XqLPmv+9qHdMF9/8p8DuNPqblr2ZvcZ+Zbu/uOaA83b6m3P2ouz8W3p4EdhPMIL2QdwJ3u3vW3fcDe4DXmNkaoNfdv+vBb+nvgZ+c95y7wtv/B3hL+d25Subv/64Fr9voWt8C7HX3Fy9Sf93qdPcHgVPnqaHWx/CtwP3ufsrdx4D7gbcttVZ3/3d3L4TfPkww3+KC6lHrBY7phTTdMS0L9/kfgS8sto961QrN31Vyvun2dV0iMPxIcyOwPdz0q+HH0Tvt7EfnC9W5Lry9cPs5zwn/w50GLltmmQ78u5k9asHSAwCr3P1ouP+jQPnSQY2uFYIWx/z/BM14TKE+x7AWf+O/SNDaK9tsZo+b2bfM7I3z6mlUrbX+fVf7mL4ROO7uL8zb1tBj2uzBXdF0+5q9uFk38E/AR9x9Avgr4ArgBuAowccnuHCdi9VfzZ/t9e5+E/CjwIfM7E2LPLahtVowiesdwBfDTc16TBdTzdqqWrOZfQwoAJ8PNx0FNrr7jcB/BbaZWW8Da63H77vafwfv5tyGRsOPabMHd8Om25tZkiC0P+/u9wK4+3F3L7p7Cfhbgq6cxeo8xLkfWefXf+Y5ZpYA+qj8Y2YrkPkAAAR7SURBVOU53P1I+O8I8KWwruPhR7fyR7iRZqiV4M3lMXc/HtbclMc0VI9jWLW/8fDE1o8D7wk/qhN2PZwMbz9K0Hf8fY2qtU6/72oe0wTwU8A9836Gxh/Ti3WCN/KLYGbnPoKTFeWTk9fW4XWNoH/qzxdsXzPv9n8h6JMDuJZzT6zs4+yJlR3Aazl7suLt4fYPce7Jin9cZq1dQM+8298h6CP7BOeeWPvjRtcaPv9u4P3NeExZcNKpHseQ4KTUfoITUwPh7cFl1Po2gqWWhxY8bmhebVuAw+X916PW89RZ8993tY7pvOP6rWY6pu7e3MEd/mBvJxjVsRf4WJ1e8w0EH1eeBHaFX28H/gF4Ktx+34I/wo+FNT5HeCY53L4VeDq87y85O1s1TdBdsIfgTPSWZda6JfyDfwJ4pnyMCPrPvg68EP472AS1ZoCTQN+8bU1xTAk+Ch8F8gStoA/U6xgS9EnvCb/ev8xa9xD0lZb/Xssh8dPh38UTwGPAT9Sr1gvUWZffdzWOabj9s8AvL3hsw45p+UtT3kVEIqbZ+7hFRGQBBbeISMQouEVEIkbBLSISMQpuEZGIUXBL1ZlZMVw17Wkz+6KZZZphX9VgZr9gZqNhTd8zsw9e4HHvsDqtZintR8EttTDr7je4+3VADvjlSp4Uziir5b6q5R53vwF4M/CHZrZq4Wu7+33u/kc1rEHamIJbau3bwJVm1hUuKrQjXJznnXCmBftFM/sK8O/V3JeZrTGzB+e12N8YPu7d4ZrJT5vZ7eWdm9mUmf0PM3vCzB5eGMgLebDEwF7gcjP7rJn9mZl9E7g9rOUvw/2usmCN7CfCr9eF23/OzB4J6/sbM4sv5wBL+1FwS82Erd4fJZgp9zHgG+7+auAHgU+YWVf40O8H3ufut1R5X7cC/xa2jq8HdpnZWoL1qm8hWOjo1WZWXnqzC3jY3a8HHgTO2w0yr6YtBDNX94Sbvg/4IXf/9QUP/STBtOnrCdZ8fsbMrgF+hmCBsBuAIvCexV5PpKyWHyelfXVaeLUQglbyZwjWUHmHmf1GuD0NbAxv3+/uF1oM6lL2tQO4M1ww7J/dfZeZ3QI84O6jAGb2eYJF9P+ZoCvmq+FzHwV++AI1/YyZvQHIAv/J3U8FSyvzRXcvnufxtwA/DxDef9rM3gu8CtgRPreTs4tYiSxKwS21MBu2Is+wIJ1+2t2fW7D9ZmC6Fvty9wfDJW5/DPgHM/sEMLHIa+X97BoQRS78/+Med//V82xf7OdYyIC73P2jS3iOCKCuEqmffwN+LQxdzOzGWu/LzC4HRtz9bwla6jcRXBDjB8xsRdin/G7gW5dQSyW+DvxKWFM8XLv568B/MLOV4fbBsF6Ri1JwS718HEgCT1pwQdaP12Ffbybo136cYEW3v/DgSjYfBb5JuLqbu3/5EmqpxIeBHzSzpwi6YK519+8Bv01wEvVJgktWralxHdIitDqgiEjEqMUtIhIxCm4RkYhRcIuIRIyCW0QkYhTcIiIRo+AWEYkYBbeISMT8f+8AqH17py8zAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Checking skewness for dependent Variable. It shows the dependent variable is 'right skewed'. \n",
    "sns.distplot(df['Per Person Price'])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Log transformed dependent variable\n",
    "sns.distplot(np.log1p(df['Per Person Price']))\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Preprocessing and Feature Engineering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 'Places Covered' was similar to 'Destination' hence removed and 'Uniq Id'  was completely unique for all rows therefore did not make sense to be used\n",
    "df2.drop(['Places Covered', 'Uniq Id'], axis=1, inplace=True)\n",
    " \n",
    "test.drop(['Places Covered', 'Uniq Id'], axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Feature containing total destinations covered in a trip\n",
    "df2['Total Destinations Covered'] = df2['Destination'].apply(lambda x: len(x.split('|')))\n",
    "\n",
    "test['Total Destinations Covered'] = test['Destination'].apply(lambda x: len(x.split('|')))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Feature containing total no. of sightseeing places covered in a trip\n",
    "df2['Total Sightseeing Places Covered'] = df2['Sightseeing Places Covered'].apply(lambda x: len(x.split('|')) if x != 'Not Available' else -1)\n",
    "\n",
    "test['Total Sightseeing Places Covered'] = test['Sightseeing Places Covered'].apply(lambda x: len(x.split('|')) if x != 'Not Available' else -1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Feature having total no. of days in respective trips\n",
    "df2['Total days'] = df2['Itinerary'].apply(lambda x: sum(int(i) for i in (re.findall(r'[0-9]', x))))\n",
    "\n",
    "test['Total days'] = test['Itinerary'].apply(lambda x: sum(int(i) for i in (re.findall(r'[0-9]', x))))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Replacing some ratings in word form to respective number in 'Hotel Details'\n",
    "df2['Hotel Details'] = df2['Hotel Details'].apply(lambda x:  x.replace('Four', '4'))\n",
    "df2['Hotel Details'] = df2['Hotel Details'].apply(lambda x:  x.replace('One', '1'))\n",
    "df2['Hotel Details'] = df2['Hotel Details'].apply(lambda x:  x.replace('Two', '2'))\n",
    "df2['Hotel Details'] = df2['Hotel Details'].apply(lambda x:  x.replace('Three', '3'))\n",
    "df2['Hotel Details'] = df2['Hotel Details'].apply(lambda x:  x.replace('Five', '5'))\n",
    "\n",
    "test['Hotel Details'] = test['Hotel Details'].apply(lambda x:  x.replace('Four', '4'))\n",
    "test['Hotel Details'] = test['Hotel Details'].apply(lambda x:  x.replace('One', '1'))\n",
    "test['Hotel Details'] = test['Hotel Details'].apply(lambda x:  x.replace('Two', '2'))\n",
    "test['Hotel Details'] = test['Hotel Details'].apply(lambda x:  x.replace('Three', '3'))\n",
    "test['Hotel Details'] = test['Hotel Details'].apply(lambda x:  x.replace('Five', '5'))\n",
    "\n",
    "# Using Regular Expression to obtain Average Rating of Hotels for each trip\n",
    "df2['Avg Rating'] = df2['Hotel Details'].apply(lambda x: sum(float(i.replace(':', '')) for i in (re.findall(r'[:][0-9]*[.]?[0-9]+', x))) / len(re.findall(r'[:][0-9]*[.]?[0-9]+', x)) if len(re.findall(r'[:][0-9]*[.]?[0-9]+', x)) != 0 else -1)\n",
    "\n",
    "test['Avg Rating'] = test['Hotel Details'].apply(lambda x: sum(float(i.replace(':', '')) for i in (re.findall(r'[:][0-9]*[.]?[0-9]+', x))) / len(re.findall(r'[:][0-9]*[.]?[0-9]+', x)) if len(re.findall(r'[:][0-9]*[.]?[0-9]+', x)) != 0 else -1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dropping date features improved score\n",
    "df2.drop('Travel Date', axis=1, inplace=True)\n",
    "test.drop('Travel Date', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import OrdinalEncoder\n",
    "\n",
    "oe = OrdinalEncoder(handle_unknown='use_encoded_value', unknown_value=-999)\n",
    "\n",
    "\n",
    "# Encoding function for few catgeorical features\n",
    "def ordinal_enc(df, col, testing=False):\n",
    "    if testing == False:\n",
    "        df[col] = oe.fit_transform(df[col])\n",
    "        \n",
    "    else:\n",
    "        df[col] = oe.transform(df[col])\n",
    "    return df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "cat_feature = ['Start City', 'Package Type', 'Cancellation Rules', 'Destination']\n",
    "\n",
    "# Ordinal Encoding 'cat_feature' columns \n",
    "df2 = ordinal_enc(df2, cat_feature)\n",
    "test = ordinal_enc(test, cat_feature, testing=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Ratio feature of 'Total Sightseeing Places Covered' and 'Total days'\n",
    "df2['Sightseeing per days'] = df2['Total Sightseeing Places Covered'] / (df2['Total days']) \n",
    "\n",
    "# Ratio feature of 'Total Destinations Covered' and 'Total days'\n",
    "df2['total destination per days'] = df2['Total Destinations Covered'] / (df2['Total days'])\n",
    "\n",
    "\n",
    "test['Sightseeing per days'] = test['Total Sightseeing Places Covered'] / test['Total days']\n",
    "test['total destination per days'] = test['Total Destinations Covered'] / test['Total days']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.feature_extraction.text import CountVectorizer\n",
    "\n",
    "# Extracting features from text columns using CountVectorizer\n",
    "def CountVect(column, train, test):\n",
    "    vect = CountVectorizer()\n",
    "    \n",
    "    train_feature = vect.fit_transform(train[column])\n",
    "    train_feature = pd.DataFrame(train_feature.todense(), columns=[(column+str(i)) for i in range(len(vect.get_feature_names()))])\n",
    "    train = pd.concat([train, train_feature], axis=1)\n",
    "    \n",
    "    test_feature = vect.transform(test[column])\n",
    "    test_feature = pd.DataFrame(test_feature.todense(), columns=[(column+str(i)) for i in range(len(vect.get_feature_names()))])\n",
    "    test = pd.concat([test, test_feature], axis=1)\n",
    "    \n",
    "    return train, test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calling 'CountVec' function for these columns\n",
    "for column in ['Sightseeing Places Covered', 'Hotel Details', 'Package Name', 'Itinerary', 'Airline']:\n",
    "    df2, test = CountVect(column, df2, test)    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dropping columns after text feature extraction\n",
    "df2.drop(['Sightseeing Places Covered', 'Hotel Details', 'Package Name', 'Itinerary', 'Airline'], axis=1, inplace=True)\n",
    "\n",
    "test.drop(['Sightseeing Places Covered', 'Hotel Details', 'Package Name', 'Itinerary', 'Airline'], axis=1, inplace=True) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Package Type</th>\n",
       "      <th>Destination</th>\n",
       "      <th>Start City</th>\n",
       "      <th>Flight Stops</th>\n",
       "      <th>Meals</th>\n",
       "      <th>Cancellation Rules</th>\n",
       "      <th>Total Destinations Covered</th>\n",
       "      <th>Total Sightseeing Places Covered</th>\n",
       "      <th>Total days</th>\n",
       "      <th>Avg Rating</th>\n",
       "      <th>...</th>\n",
       "      <th>Airline53</th>\n",
       "      <th>Airline54</th>\n",
       "      <th>Airline55</th>\n",
       "      <th>Airline56</th>\n",
       "      <th>Airline57</th>\n",
       "      <th>Airline58</th>\n",
       "      <th>Airline59</th>\n",
       "      <th>Airline60</th>\n",
       "      <th>Airline61</th>\n",
       "      <th>Airline62</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Luxury</td>\n",
       "      <td>Goa</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>1</td>\n",
       "      <td>-1</td>\n",
       "      <td>5</td>\n",
       "      <td>4.10</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Luxury</td>\n",
       "      <td>Bandipur</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>This cancellation policy is applicable for boo...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>4.40</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Standard</td>\n",
       "      <td>Munnar</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>This cancellation policy is applicable for boo...</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>-1.00</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Deluxe</td>\n",
       "      <td>Munnar</td>\n",
       "      <td>Mumbai</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>This cancellation policy is applicable for boo...</td>\n",
       "      <td>1</td>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>-1.00</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Luxury</td>\n",
       "      <td>Cochin|Munnar|Thekkady|Allepey</td>\n",
       "      <td>New Delhi</td>\n",
       "      <td>0</td>\n",
       "      <td>4</td>\n",
       "      <td>Cancellation any time after making the 1st pay...</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>5</td>\n",
       "      <td>4.55</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 4312 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Package Type                     Destination Start City  Flight Stops  \\\n",
       "0       Luxury                             Goa  New Delhi             0   \n",
       "1       Luxury                        Bandipur  New Delhi             0   \n",
       "2     Standard                          Munnar  New Delhi             2   \n",
       "3       Deluxe                          Munnar     Mumbai             1   \n",
       "4       Luxury  Cochin|Munnar|Thekkady|Allepey  New Delhi             0   \n",
       "\n",
       "   Meals                                 Cancellation Rules  \\\n",
       "0      4  Cancellation any time after making the 1st pay...   \n",
       "1      4  This cancellation policy is applicable for boo...   \n",
       "2      3  This cancellation policy is applicable for boo...   \n",
       "3      3  This cancellation policy is applicable for boo...   \n",
       "4      4  Cancellation any time after making the 1st pay...   \n",
       "\n",
       "   Total Destinations Covered  Total Sightseeing Places Covered  Total days  \\\n",
       "0                           1                                -1           5   \n",
       "1                           1                                 1           2   \n",
       "2                           1                                 4           3   \n",
       "3                           1                                 6           3   \n",
       "4                           4                                10           5   \n",
       "\n",
       "   Avg Rating  ...  Airline53  Airline54  Airline55  Airline56  Airline57  \\\n",
       "0        4.10  ...          0          0          0          0          0   \n",
       "1        4.40  ...          0          0          0          0          0   \n",
       "2       -1.00  ...          0          0          0          0          0   \n",
       "3       -1.00  ...          0          0          0          0          0   \n",
       "4        4.55  ...          0          0          0          0          0   \n",
       "\n",
       "   Airline58  Airline59  Airline60  Airline61  Airline62  \n",
       "0          0          0          0          0          0  \n",
       "1          0          0          0          0          0  \n",
       "2          0          0          0          0          0  \n",
       "3          0          0          0          0          0  \n",
       "4          0          0          0          0          0  \n",
       "\n",
       "[5 rows x 4312 columns]"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(21000, 4313)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df2.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model Selection"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.model_selection import KFold\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.metrics import mean_squared_log_error\n",
    "from sklearn.linear_model import LinearRegression\n",
    "from sklearn.ensemble import ExtraTreesRegressor\n",
    "from sklearn.ensemble import GradientBoostingRegressor\n",
    "from catboost import CatBoostRegressor\n",
    "from sklearn.linear_model import LassoCV, ElasticNet\n",
    "from sklearn.linear_model import RidgeCV\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from category_encoders import MEstimateEncoder\n",
    "from sklearn.ensemble import StackingRegressor\n",
    "from sklearn.ensemble import VotingRegressor\n",
    "from sklearn.neighbors import KNeighborsRegressor\n",
    "from sklearn.preprocessing import OrdinalEncoder\n",
    "from sklearn.svm import SVR\n",
    "import lightgbm as lgb\n",
    "import xgboost as xgb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Separating and storing independent and dependent variable in X and y respectively\n",
    "X, y = df2.drop('Per Person Price', axis=1), df2['Per Person Price']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Stacking regressor function to ensemble LGBM and CatBoost\n",
    "def get_stacking():\n",
    "    level0 = [('lgbm_regressor', lgb.LGBMRegressor(n_estimators=3000, max_depth=11, learning_rate=0.06, num_leaves=40)),\n",
    "               #('XGB_regressor', xgb.XGBRegressor(n_estimators=700, objective='reg:squarederror', max_depth=7, learning_rate=0.06, colsample_bytree=0.9, subsample=0.8)),\n",
    "               ('catboost', CatBoostRegressor(silent=True,learning_rate=0.18, n_estimators=2000, depth=6))]\n",
    "    \n",
    "    level1 = LinearRegression()\n",
    "    model = StackingRegressor(estimators=level0, final_estimator=level1, cv=5)\n",
    "    return model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# LGBM performance "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RMSLE score for fold 1 is 0.16425209762557386\n",
      "RMSLE score for fold 2 is 0.15850760104442105\n",
      "RMSLE score for fold 3 is 0.15532924859255232\n",
      "RMSLE score for fold 4 is 0.16707937948463222\n",
      "RMSLE score for fold 5 is 0.15356497957272838\n",
      "RMSLE score for fold 6 is 0.17381062747283751\n",
      "RMSLE score for fold 7 is 0.1471130876311855\n",
      "RMSLE score for fold 8 is 0.16153380182075983\n",
      "RMSLE score for fold 9 is 0.14817993517581438\n",
      "RMSLE score for fold 10 is 0.1556281967004952\n",
      "Mean RMSLE score is 0.15849989551210003\n"
     ]
    }
   ],
   "source": [
    "# K-Fold Cross Validation \n",
    "kf = KFold(n_splits=10, shuffle=True)\n",
    "scores = []\n",
    "for fold, (train_index, test_index) in enumerate(kf.split(X, y), 1):\n",
    "    X_train = X.iloc[train_index]\n",
    "    X_train = ordinal_enc(X_train, cat_feature)\n",
    "    \n",
    "    y_train = np.log1p(y.iloc[train_index])\n",
    "    \n",
    "    X_test = X.iloc[test_index]\n",
    "    X_test = ordinal_enc(X_test, cat_feature, testing=True)\n",
    "\n",
    "    y_test = y.iloc[test_index]\n",
    "    \n",
    "    #model = GradientBoostingRegressor(n_estimators=1000, learning_rate=0.03)\n",
    "    #model = RandomForestRegressor(n_estimators=200, n_jobs=-1)\n",
    "    #model = ElasticNet()\n",
    "    model = lgb.LGBMRegressor(n_estimators=2500, max_depth=11, learning_rate=0.05, num_leaves=40)\n",
    "    #model = xgb.XGBRegressor(n_estimators=590, objective='reg:squarederror', max_depth=7, learning_rate=0.06, min_child_weight=1.2)\n",
    "    #model = get_stacking()\n",
    "    #model = ExtraTreesRegressor(n_estimators=500, bootstrap=True, n_jobs=-1)\n",
    "    #model = LinearRegression()\n",
    "    #model = KNeighborsRegressor(weights='distance', n_neighbors=15)\n",
    "    #model = CatBoostRegressor(silent=True,learning_rate=0.18, n_estimators=1700, depth=6)\n",
    "    model.fit(X_train, y_train)\n",
    "    \n",
    "    pred = model.predict(X_test)\n",
    " \n",
    "    score = np.sqrt(mean_squared_log_error(y_test, np.expm1((pred))))\n",
    "    print(f'RMSLE score for fold {fold} is {score}')\n",
    "    scores.append(score)\n",
    "\n",
    "print(f'Mean RMSLE score is {np.mean(scores)}')     "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Model Training and Prediction"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 300,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Stack Model \n",
    "model = get_stacking() # <-- Performed Best"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 301,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "StackingRegressor(cv=5,\n",
       "                  estimators=[('lgbm_regressor',\n",
       "                               LGBMRegressor(learning_rate=0.06, max_depth=11,\n",
       "                                             n_estimators=3000,\n",
       "                                             num_leaves=40)),\n",
       "                              ('catboost',\n",
       "                               <catboost.core.CatBoostRegressor object at 0x0000024DA3385188>)],\n",
       "                  final_estimator=LinearRegression())"
      ]
     },
     "execution_count": 301,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Log transforming Target Variable before training\n",
    "y_ = np.log1p(y)\n",
    "\n",
    "# Model Training\n",
    "model.fit(X, y_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 302,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Making Predictions and using 'expm1' to convert it back to original form\n",
    "sub = pd.DataFrame(np.expm1(model.predict(test)), columns=['Per Person Price'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 303,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Saving Predictions\n",
    "sub.to_csv('sub_ensembleSTACK_lgb_catboost_lr_countvec.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 304,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Per Person Price</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>19389.820849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11832.206036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>5352.769612</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>7219.301968</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>21585.722077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8995</th>\n",
       "      <td>11955.815337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8996</th>\n",
       "      <td>15526.501926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8997</th>\n",
       "      <td>16477.858873</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8998</th>\n",
       "      <td>21026.495452</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8999</th>\n",
       "      <td>9446.645048</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9000 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Per Person Price\n",
       "0         19389.820849\n",
       "1         11832.206036\n",
       "2          5352.769612\n",
       "3          7219.301968\n",
       "4         21585.722077\n",
       "...                ...\n",
       "8995      11955.815337\n",
       "8996      15526.501926\n",
       "8997      16477.858873\n",
       "8998      21026.495452\n",
       "8999       9446.645048\n",
       "\n",
       "[9000 rows x 1 columns]"
      ]
     },
     "execution_count": 304,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sub"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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